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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
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High accuracy indoor positioning system using Galois field-based cryptography and hybrid deep learning.

Mohammad Mazyad Hazzazi1, Prashant Kumar Shukla2, Piyush Kumar Shukla3

  • 1Department of Mathematics, College of Science, King Khalid University, 61413, Abha, Saudi Arabia.

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Summary

This study introduces a novel indoor positioning system (IPS) using deep learning and advanced security features. The system achieves high accuracy and resilience for reliable indoor location tracking in complex environments.

Keywords:
Blockchain technologyDeep learningFingerprintingGalois field cryptographyHybrid optimizationIndoor positioning systemQR codes

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Cybersecurity

Background:

  • Global Positioning System (GPS) is ineffective in indoor environments.
  • Traditional indoor positioning systems (IPS) face challenges in accuracy, resilience, and security due to environmental complexity and signal noise.
  • Smart manufacturing and logistics require robust indoor location solutions.

Purpose of the Study:

  • To develop an accurate, resilient, and secure indoor positioning system.
  • To leverage deep learning and advanced cryptographic techniques for enhanced IPS performance.
  • To address the limitations of traditional IPS in complex indoor settings.

Main Methods:

  • Utilized a two-phase approach: offline data collection and online location classification.
  • Employed signal processing for noise reduction and data augmentation, followed by DBSCAN clustering.
  • Developed the Deep Spatial-Temporal Attention Network (Deep-STAN), a hybrid model combining CNNs, ViTs, and LSTMs with attention mechanisms.
  • Integrated Elliptic Curve Cryptography (ECC) for data encryption, QR codes for location marking, and blockchain for immutable data storage.

Main Results:

  • Achieved high performance metrics: accuracy of 0.9937, precision of 0.987, sensitivity of 0.9898, and specificity of 0.9878.
  • Demonstrated sustained accuracy (0.9804) even with 80% data usage, indicating model stability.
  • The integrated ECC, QR codes, and blockchain significantly enhanced data integrity, confidentiality, and system resilience.

Conclusions:

  • The proposed deep learning-based IPS with advanced security features offers a stable and flexible solution for indoor positioning.
  • The hybrid Deep-STAN model and cryptographic enhancements provide superior accuracy and security compared to traditional methods.
  • The system is well-suited for real-world applications requiring low-latency, secure, and reliable indoor location services.